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63 vulnerabilities by lfprojects
CVE-2025-65105 (GCVE-0-2025-65105)
Vulnerability from cvelistv5 – Published: 2025-12-02 17:49 – Updated: 2025-12-02 18:46
VLAI?
Summary
Apptainer is an open source container platform. In Apptainer versions less than 1.4.5, a container can disable two of the forms of the little used --security option, in particular the forms --security=apparmor:<profile> and --security=selinux:<label> which otherwise put restrictions on operations that containers can do. The --security option has always been mentioned in Apptainer documentation as being a feature for the root user, although these forms do also work for unprivileged users on systems where the corresponding feature is enabled. Apparmor is enabled by default on Debian-based distributions and SElinux is enabled by default on RHEL-based distributions, but on SUSE it depends on the distribution version. This vulnerability is fixed in 1.4.5.
Severity ?
4.5 (Medium)
CWE
Assigner
References
| URL | Tags | |||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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CVE-2025-11200 (GCVE-0-2025-11200)
Vulnerability from cvelistv5 – Published: 2025-10-29 19:42 – Updated: 2025-10-31 03:55
VLAI?
Summary
MLflow Weak Password Requirements Authentication Bypass Vulnerability. This vulnerability allows remote attackers to bypass authentication on affected installations of MLflow. Authentication is not required to exploit this vulnerability.
The specific flaw exists within the handling of passwords. The issue results from weak password requirements. An attacker can leverage this vulnerability to bypass authentication on the system. Was ZDI-CAN-26916.
Severity ?
8.1 (High)
CWE
- CWE-521 - Weak Password Requirements
Assigner
References
| URL | Tags | |||||||
|---|---|---|---|---|---|---|---|---|
|
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CVE-2025-11201 (GCVE-0-2025-11201)
Vulnerability from cvelistv5 – Published: 2025-10-29 19:37 – Updated: 2025-10-31 03:55
VLAI?
Summary
MLflow Tracking Server Model Creation Directory Traversal Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of MLflow Tracking Server. Authentication is not required to exploit this vulnerability.
The specific flaw exists within the handling of model file paths. The issue results from the lack of proper validation of a user-supplied path prior to using it in file operations. An attacker can leverage this vulnerability to execute code in the context of the service account. Was ZDI-CAN-26921.
Severity ?
8.1 (High)
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
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CVE-2025-49844 (GCVE-0-2025-49844)
Vulnerability from cvelistv5 – Published: 2025-10-03 19:27 – Updated: 2025-11-04 21:11
VLAI?
Summary
Redis is an open source, in-memory database that persists on disk. Versions 8.2.1 and below allow an authenticated user to use a specially crafted Lua script to manipulate the garbage collector, trigger a use-after-free and potentially lead to remote code execution. The problem exists in all versions of Redis with Lua scripting. This issue is fixed in version 8.2.2. To workaround this issue without patching the redis-server executable is to prevent users from executing Lua scripts. This can be done using ACL to restrict EVAL and EVALSHA commands.
Severity ?
10 (Critical)
CWE
- CWE-416 - Use After Free
Assigner
References
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CVE-2025-52967 (GCVE-0-2025-52967)
Vulnerability from cvelistv5 – Published: 2025-06-23 00:00 – Updated: 2025-06-23 20:12
VLAI?
Summary
gateway_proxy_handler in MLflow before 3.1.0 lacks gateway_path validation.
Severity ?
5.8 (Medium)
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| lfprojects | MLflow |
Affected:
0 , < 3.1.0
(semver)
|
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CVE-2025-21605 (GCVE-0-2025-21605)
Vulnerability from cvelistv5 – Published: 2025-04-23 15:38 – Updated: 2025-06-02 03:54
VLAI?
Summary
Redis is an open source, in-memory database that persists on disk. In versions starting at 2.6 and prior to 7.4.3, An unauthenticated client can cause unlimited growth of output buffers, until the server runs out of memory or is killed. By default, the Redis configuration does not limit the output buffer of normal clients (see client-output-buffer-limit). Therefore, the output buffer can grow unlimitedly over time. As a result, the service is exhausted and the memory is unavailable. When password authentication is enabled on the Redis server, but no password is provided, the client can still cause the output buffer to grow from "NOAUTH" responses until the system will run out of memory. This issue has been patched in version 7.4.3. An additional workaround to mitigate this problem without patching the redis-server executable is to block access to prevent unauthenticated users from connecting to Redis. This can be done in different ways. Either using network access control tools like firewalls, iptables, security groups, etc, or enabling TLS and requiring users to authenticate using client side certificates.
Severity ?
7.5 (High)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
| URL | Tags | |||||||
|---|---|---|---|---|---|---|---|---|
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CVE-2025-0453 (GCVE-0-2025-0453)
Vulnerability from cvelistv5 – Published: 2025-03-20 10:11 – Updated: 2025-10-15 12:50
VLAI?
Summary
In mlflow/mlflow version 2.17.2, the `/graphql` endpoint is vulnerable to a denial of service attack. An attacker can create large batches of queries that repeatedly request all runs from a given experiment. This can tie up all the workers allocated by MLFlow, rendering the application unable to respond to other requests. This vulnerability is due to uncontrolled resource consumption.
Severity ?
5.9 (Medium)
CWE
- CWE-410 - Insufficient Resource Pool
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , ≤ latest
(custom)
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CVE-2025-1474 (GCVE-0-2025-1474)
Vulnerability from cvelistv5 – Published: 2025-03-20 10:10 – Updated: 2025-03-20 18:22
VLAI?
Summary
In mlflow/mlflow version 2.18, an admin is able to create a new user account without setting a password. This vulnerability could lead to security risks, as accounts without passwords may be susceptible to unauthorized access. Additionally, this issue violates best practices for secure user account management. The issue is fixed in version 2.19.0.
Severity ?
CWE
- CWE-521 - Weak Password Requirements
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.19.0
(custom)
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CVE-2025-1473 (GCVE-0-2025-1473)
Vulnerability from cvelistv5 – Published: 2025-03-20 10:10 – Updated: 2025-03-20 18:22
VLAI?
Summary
A Cross-Site Request Forgery (CSRF) vulnerability exists in the Signup feature of mlflow/mlflow versions 2.17.0 to 2.20.1. This vulnerability allows an attacker to create a new account, which may be used to perform unauthorized actions on behalf of the malicious user.
Severity ?
5.4 (Medium)
CWE
- CWE-352 - Cross-Site Request Forgery (CSRF)
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.20.2
(custom)
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CVE-2024-8859 (GCVE-0-2024-8859)
Vulnerability from cvelistv5 – Published: 2025-03-20 10:09 – Updated: 2025-03-20 18:33
VLAI?
Summary
A path traversal vulnerability exists in mlflow/mlflow version 2.15.1. When users configure and use the dbfs service, concatenating the URL directly into the file protocol results in an arbitrary file read vulnerability. This issue occurs because only the path part of the URL is checked, while parts such as query and parameters are not handled. The vulnerability is triggered if the user has configured the dbfs service, and during usage, the service is mounted to a local directory.
Severity ?
7.5 (High)
CWE
- CWE-29 - Path Traversal: '\..\filename'
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.17.0
(custom)
|
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CVE-2024-6838 (GCVE-0-2024-6838)
Vulnerability from cvelistv5 – Published: 2025-03-20 10:09 – Updated: 2025-03-20 14:25
VLAI?
Summary
In mlflow/mlflow version v2.13.2, a vulnerability exists that allows the creation or renaming of an experiment with a large number of integers in its name due to the lack of a limit on the experiment name. This can cause the MLflow UI panel to become unresponsive, leading to a potential denial of service. Additionally, there is no character limit in the `artifact_location` parameter while creating the experiment.
Severity ?
5.3 (Medium)
CWE
- CWE-400 - Uncontrolled Resource Consumption
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , ≤ latest
(custom)
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CVE-2024-27134 (GCVE-0-2024-27134)
Vulnerability from cvelistv5 – Published: 2024-11-25 13:48 – Updated: 2024-11-25 14:23
VLAI?
Summary
Excessive directory permissions in MLflow leads to local privilege escalation when using spark_udf. This behavior can be exploited by a local attacker to gain elevated permissions by using a ToCToU attack. The issue is only relevant when the spark_udf() MLflow API is called.
Severity ?
CWE
Assigner
References
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|---|---|---|
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CVE-2024-2928 (GCVE-0-2024-2928)
Vulnerability from cvelistv5 – Published: 2024-06-06 18:29 – Updated: 2024-08-01 19:32
VLAI?
Summary
A Local File Inclusion (LFI) vulnerability was identified in mlflow/mlflow, specifically in version 2.9.2, which was fixed in version 2.11.3. This vulnerability arises from the application's failure to properly validate URI fragments for directory traversal sequences such as '../'. An attacker can exploit this flaw by manipulating the fragment part of the URI to read arbitrary files on the local file system, including sensitive files like '/etc/passwd'. The vulnerability is a bypass to a previous patch that only addressed similar manipulation within the URI's query string, highlighting the need for comprehensive validation of all parts of a URI to prevent LFI attacks.
Severity ?
7.5 (High)
CWE
- CWE-29 - Path Traversal: '\..\filename'
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.11.3
(custom)
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CVE-2024-0520 (GCVE-0-2024-0520)
Vulnerability from cvelistv5 – Published: 2024-06-06 18:19 – Updated: 2025-10-15 12:50
VLAI?
Summary
A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.http_dataset_source.py` module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the `Content-Disposition` header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0.
Severity ?
10 (Critical)
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.9.0
(custom)
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CVE-2024-3099 (GCVE-0-2024-3099)
Vulnerability from cvelistv5 – Published: 2024-06-06 18:08 – Updated: 2024-08-01 19:32
VLAI?
Summary
A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.
Severity ?
5.4 (Medium)
CWE
- CWE-475 - Undefined Behavior for Input to API
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
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(custom)
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CVE-2024-37061 (GCVE-0-2024-37061)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:02 – Updated: 2024-08-02 03:43
VLAI?
Summary
Remote Code Execution can occur in versions of the MLflow platform running version 1.11.0 or newer, enabling a maliciously crafted MLproject to execute arbitrary code on an end user’s system when run.
Severity ?
8.8 (High)
CWE
- CWE-94 - Improper Control of Generation of Code ('Code Injection')
Assigner
References
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CVE-2024-37060 (GCVE-0-2024-37060)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:02 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.27.0 or newer, enabling a maliciously crafted Recipe to execute arbitrary code on an end user’s system when run.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37059 (GCVE-0-2024-37059)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:01 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.5.0 or newer, enabling a maliciously uploaded PyTorch model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37058 (GCVE-0-2024-37058)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:01 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.5.0 or newer, enabling a maliciously uploaded Langchain AgentExecutor model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37057 (GCVE-0-2024-37057)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:01 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37056 (GCVE-0-2024-37056)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:01 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.23.0 or newer, enabling a maliciously uploaded LightGBM scikit-learn model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37055 (GCVE-0-2024-37055)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:00 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.24.0 or newer, enabling a maliciously uploaded pmdarima model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37054 (GCVE-0-2024-37054)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:00 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37053 (GCVE-0-2024-37053)
Vulnerability from cvelistv5 – Published: 2024-06-04 12:00 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-37052 (GCVE-0-2024-37052)
Vulnerability from cvelistv5 – Published: 2024-06-04 11:59 – Updated: 2024-08-02 03:43
VLAI?
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
Severity ?
8.8 (High)
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-4263 (GCVE-0-2024-4263)
Vulnerability from cvelistv5 – Published: 2024-05-16 09:03 – Updated: 2024-08-01 20:33
VLAI?
Summary
A broken access control vulnerability exists in mlflow/mlflow versions before 2.10.1, where low privilege users with only EDIT permissions on an experiment can delete any artifacts. This issue arises due to the lack of proper validation for DELETE requests by users with EDIT permissions, allowing them to perform unauthorized deletions of artifacts. The vulnerability specifically affects the handling of artifact deletions within the application, as demonstrated by the ability of a low privilege user to delete a directory inside an artifact using a DELETE request, despite the official documentation stating that users with EDIT permission can only read and update artifacts, not delete them.
Severity ?
5.4 (Medium)
CWE
- CWE-284 - Improper Access Control
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.10.1
(custom)
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CVE-2024-3848 (GCVE-0-2024-3848)
Vulnerability from cvelistv5 – Published: 2024-05-16 09:03 – Updated: 2024-08-01 20:26
VLAI?
Summary
A path traversal vulnerability exists in mlflow/mlflow version 2.11.0, identified as a bypass for the previously addressed CVE-2023-6909. The vulnerability arises from the application's handling of artifact URLs, where a '#' character can be used to insert a path into the fragment, effectively skipping validation. This allows an attacker to construct a URL that, when processed, ignores the protocol scheme and uses the provided path for filesystem access. As a result, an attacker can read arbitrary files, including sensitive information such as SSH and cloud keys, by exploiting the way the application converts the URL into a filesystem path. The issue stems from insufficient validation of the fragment portion of the URL, leading to arbitrary file read through path traversal.
Severity ?
7.5 (High)
CWE
- CWE-29 - Path Traversal: '\..\filename'
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.12.1
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CVE-2024-1594 (GCVE-0-2024-1594)
Vulnerability from cvelistv5 – Published: 2024-04-16 00:00 – Updated: 2024-08-01 18:48
VLAI?
Summary
A path traversal vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the `artifact_location` parameter when creating an experiment. Attackers can exploit this vulnerability by using a fragment component `#` in the artifact location URI to read arbitrary files on the server in the context of the server's process. This issue is similar to CVE-2023-6909 but utilizes a different component of the URI to achieve the same effect.
Severity ?
7.5 (High)
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , ≤ latest
(custom)
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CVE-2024-3573 (GCVE-0-2024-3573)
Vulnerability from cvelistv5 – Published: 2024-04-16 00:00 – Updated: 2024-08-01 20:12
VLAI?
Summary
mlflow/mlflow is vulnerable to Local File Inclusion (LFI) due to improper parsing of URIs, allowing attackers to bypass checks and read arbitrary files on the system. The issue arises from the 'is_local_uri' function's failure to properly handle URIs with empty or 'file' schemes, leading to the misclassification of URIs as non-local. Attackers can exploit this by crafting malicious model versions with specially crafted 'source' parameters, enabling the reading of sensitive files within at least two directory levels from the server's root.
Severity ?
9.3 (Critical)
CWE
- CWE-29 - Path Traversal: '\..\filename'
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , < 2.10.0
(custom)
|
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CVE-2024-1558 (GCVE-0-2024-1558)
Vulnerability from cvelistv5 – Published: 2024-04-16 00:00 – Updated: 2024-08-01 18:40
VLAI?
Summary
A path traversal vulnerability exists in the `_create_model_version()` function within `server/handlers.py` of the mlflow/mlflow repository, due to improper validation of the `source` parameter. Attackers can exploit this vulnerability by crafting a `source` parameter that bypasses the `_validate_non_local_source_contains_relative_paths(source)` function's checks, allowing for arbitrary file read access on the server. The issue arises from the handling of unquoted URL characters and the subsequent misuse of the original `source` value for model version creation, leading to the exposure of sensitive files when interacting with the `/model-versions/get-artifact` handler.
Severity ?
7.5 (High)
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| mlflow | mlflow/mlflow |
Affected:
unspecified , ≤ latest
(custom)
|
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